Modern GPUs are beginning to deviate from the traditional rasterization model. NVidia GPUs starting from Turing and AMD GPUs starting from RDNA2 provide a new programmable geometry pipeline that, instead of being built around index buffers and vertex shaders, is built around mesh shaders - a new shader type that allows to provide a batch of work to the rasterizer.
Using mesh shaders in context of traditional mesh rendering provides an opportunity to use a variety of optimization techniques, starting from more efficient vertex reuse, using various forms of culling (e.g. cluster frustum or occlusion culling) and in-memory compression to maximize the utilization of GPU hardware. Beyond traditional rendering mesh shaders provide a richer programming model that can synthesize new geometry more efficiently than common alternatives such as geometry shaders. Mesh shading can be accessed via Vulkan or Direct3D 12 APIs; please refer to Introduction to Turing Mesh Shaders and Mesh Shaders and Amplification Shaders: Reinventing the Geometry Pipeline for additional information.
To use mesh shaders for conventional rendering efficiently, geometry needs to be converted into a series of meshlets; each meshlet represents a small subset of the original mesh and comes with a small set of vertices and a separate micro-index buffer that references vertices in the meshlet. This information can be directly fed to the rasterizer from the mesh shader. This library provides algorithms to create meshlet data for a mesh, and - assuming geometry is static - can compute bounding information that can be used to perform cluster culling, a technique that can reject a meshlet if it's invisible on screen.
To generate meshlet data, this library provides two algorithms - meshopt_buildMeshletsScan, which creates the meshlet data using a vertex cache-optimized index buffer as a starting point by greedily aggregating consecutive triangles until they go over the meshlet limits, and meshopt_buildMeshlets, which doesn't depend on any other algorithms and tries to balance topological efficiency (by maximizing vertex reuse inside meshlets) with culling efficiency (by minimizing meshlet radius and triangle direction divergence). meshopt_buildMeshlets is recommended in cases when the resulting meshlet data will be used in cluster culling algorithms.
const size_t max_vertices = 64;
const size_t max_triangles = 124;
const float cone_weight = 0.0f;
size_t max_meshlets = meshopt_buildMeshletsBound(indices.size(), max_vertices, max_triangles);
std::vector<meshopt_Meshlet> meshlets(max_meshlets);
std::vector<unsigned int> meshlet_vertices(max_meshlets * max_vertices);
std::vector<unsigned char> meshlet_triangles(max_meshlets * max_triangles * 3);
size_t meshlet_count = meshopt_buildMeshlets(meshlets.data(), meshlet_vertices.data(), meshlet_triangles.data(), indices.data(),
indices.size(), &vertices[0].x, vertices.size(), sizeof(Vertex), max_vertices, max_triangles, cone_weight);
To generate the meshlet data, max_vertices and max_triangles need to be set within limits supported by the hardware; for NVidia the values of 64 and 124 are recommended. cone_weight should be left as 0 if cluster cone culling is not used, and set to a value between 0 and 1 to balance cone culling efficiency with other forms of culling like frustum or occlusion culling.
Each resulting meshlet refers to a portion of meshlet_vertices and meshlet_triangles arrays; this data can be uploaded to GPU and used directly after trimming:
const meshopt_Meshlet& last = meshlets[meshlet_count - 1];
meshlet_vertices.resize(last.vertex_offset + last.vertex_count);
meshlet_triangles.resize(last.triangle_offset + ((last.triangle_count * 3 + 3) & ~3));
meshlets.resize(meshlet_count);
However depending on the application other strategies of storing the data can be useful; for example, meshlet_vertices serves as indices into the original vertex buffer but it might be worthwhile to generate a mini vertex buffer for each meshlet to remove the extra indirection when accessing vertex data, or it might be desirable to compress vertex data as vertices in each meshlet are likely to be very spatially coherent.
After generating the meshlet data, it's also possible to generate extra data for each meshlet that can be saved and used at runtime to perform cluster culling, where each meshlet can be discarded if it's guaranteed to be invisible. To generate the data, meshlet_computeMeshletBounds can be used:
meshopt_Bounds bounds = meshopt_computeMeshletBounds(&meshlet_vertices[m.vertex_offset], &meshlet_triangles[m.triangle_offset],
m.triangle_count, &vertices[0].x, vertices.size(), sizeof(Vertex));
The resulting bounds values can be used to perform frustum or occlusion culling using the bounding sphere, or cone culling using the cone axis/angle (which will reject the entire meshlet if all triangles are guaranteed to be back-facing from the camera point of view):